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Urban Construction Waste Recycling Path: Robust Optimization

Autor(en): ORCID


ORCID
Medium: Fachartikel
Sprache(n): Englisch
Veröffentlicht in: Buildings, , n. 11, v. 13
Seite(n): 2802
DOI: 10.3390/buildings13112802
Abstrakt:

The world produces a huge amount of urban construction waste each year. Scientific planning of the construction waste recycling path is urgently needed to improve the recycling of construction waste. Existing construction waste recycling models do not pay sufficient attention to the uncertainty of the recycling quantity, which limits their ability to provide support for solving practical problems. The purpose of this paper is to solve the problem of uncertain recycling quantities in optimizing the urban construction waste recycling path. Thus, this paper first builds a recycling model for a deterministic environment with the economic objective as the decision criterion and the transportation flow, construction waste treatment capacity and capability, and environmental and social impact as the constraints. Then, a robust optimization method is adopted to optimize the deterministic model for the uncertainty of the recycling quantity. The data of this paper are from Nanjing, China. The validity of the model and the evolution of the recycling path are tested based on the data of Nanjing. The findings of this paper are as follows: Firstly, the robust model is cost-effective in the face of uncertainty in supply. Secondly, the robust model has greater total treatment capacity. Even in the worst-case scenario, it can guarantee a higher treatment capacity. Thirdly, both models follow the proximity principle which reduces the transportation costs and only slowly increases the total cost of the robust model. This paper provides a scientific and convenient tool to plan the recycling path of construction waste in large cities.

Copyright: © 2023 by the authors; licensee MDPI, Basel, Switzerland.
Lizenz:

Dieses Werk wurde unter der Creative-Commons-Lizenz Namensnennung 4.0 International (CC-BY 4.0) veröffentlicht und darf unter den Lizenzbedinungen vervielfältigt, verbreitet, öffentlich zugänglich gemacht, sowie abgewandelt und bearbeitet werden. Dabei muss der Urheber bzw. Rechteinhaber genannt und die Lizenzbedingungen eingehalten werden.

  • Über diese
    Datenseite
  • Reference-ID
    10753611
  • Veröffentlicht am:
    14.01.2024
  • Geändert am:
    07.02.2024
 
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